摘要
通过对数据挖掘技术的研究,笔者使用关联规则中的Apriori算法对无纸化考试系统的数据库进行了分析和挖掘,实现了对Apriori算法的改进和运算.本文的方法通过构建相关高频集,可以对不同分数等级的学生数据进行加权处理,使得高频集中的数据在数据仓库中更加明显,从而令无纸化考试系统更科学地组装试卷.
Based on the researches of the data mining technology,this paper analyses and digs the database of the paperless examination system using the association rules of Apriori algorithm and implements the improvement and computation for Apriori algorithm.By building high frequency data sets,this paper conducts a weighted approach on score data sets of different levels so that the data contained in high frequency can be observed easily in the data warehouse,ensuring that the paperless examination system can assemble test papers more scientifically.
出处
《周口师范学院学报》
CAS
2015年第2期129-131,共3页
Journal of Zhoukou Normal University
基金
福建省教育厅项目(No.JB13267)